SearchPulse AI - Google Search Console Intelligence Platform

Actionable search analytics, striking-distance keyword prioritization, traffic drop diagnostics and content decay detection.

Includes built-in synthetic 90-day e-commerce dataset for zero-config public evaluation.

View Source on GitHub →

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Overview

SearchPulse AI is an enterprise-grade Google Search Console intelligence platform built with Python 3.11, FastAPI, and Google OAuth 2.0 PKCE. It bridges the gap between raw Google Search Console data dumps and high-impact SEO execution sprints by calculating true mathematical CTR, scoring striking-distance keyword opportunities, diagnosing traffic drop root causes, and tracking content decay velocity.

Screenshot of the SearchPulse AI dashboard — SearchPulse AI intelligence dashboard featuring striking-distance keyword prioritization and root-cause diagnostic center.

Problem It Solves

Standard Google Search Console interfaces make it notoriously difficult to prioritize actions. Averages distort real CTR, page-two queries with massive search volumes get buried, and diagnosing whether a sudden traffic drop stems from technical de-indexing, algorithmic SERP loss, or seasonal shifts requires hours of manual cross-referencing.

Target Users

Heads of SEO and Digital Marketing Directors
SEO Specialists and Technical Analysts
Enterprise E-Commerce Growth Teams
Agencies managing multi-domain client portfolios

Key Features

True Mathematical CTR: Computes exact ratio of sum of clicks over sum of impressions rather than averaging position CTR percentages.
Striking-Distance Keyword Opportunities: Isolates queries in positions 8–20 with high search impression volume, comparing actual vs expected CTR curves to prioritize quick wins using ICE scoring.
Traffic Drop Diagnostics: Automatically classifies drops into technical 404/de-indexing leaks, ranking losses, seasonality, and AI Overview CTR erosion.
Content Decay Engine: Classifies URL trajectories into Acute Drop, Gradual Decay, Stagnant, and Healthy with actionable refresh blueprints.
Keyword Cannibalization Detector: Detects multi-URL conflicts splitting search visibility on identical queries.
Automated Action Center: Converts findings into prioritized sprint backlog tickets with prefilled execution links.
One-Click Reporting: Generates self-contained executive HTML audit reports and developer CSV exports.
Zero-Config Demo Mode: Ships with 90-day synthetic e-commerce Search Console fixture data for instant demonstration without live API credentials.
26 Passing Tests: 100% CI pass rate on GitHub Actions with Ruff linting and Pytest.

Technologies

Python 3.11
FastAPI
Google Search Console API
Google OAuth 2.0 PKCE
Pandas
pytest
Ruff

Contribution & Skills

Sole architect and developer. Engineered the mathematical analytics engine, OAuth 2.0 PKCE handshake, diagnostic classifiers, responsive glassmorphic dashboard UI, and automated test suite with full CI coverage.

Install & Usage

Install

git clone https://github.com/hamid-digitalmarketer/searchpulse-ai.git
cd searchpulse-ai
pip install -e .

Run Demo Dashboard

python -m uvicorn app.main:app --reload --port 8000

Run Automated Test Suite

pytest -v

Full documentation lives in the repository README →

FAQ

How does SearchPulse AI prioritize striking-distance keywords?

SearchPulse AI models an empirical Expected CTR benchmark curve across SERP positions 1-20, calculates incremental click gains, and scores each opportunity with the ICE (Impact, Confidence, Ease) framework.

What causes of traffic drops does SearchPulse AI categorize?

It isolates technical de-indexing or 404 leaks, algorithmic core update ranking losses, seasonal market interest contractions, and CTR erosion driven by Google SERP AI Overviews.